"By fostering lifelong learning, promoting our values and identity, and leveraging the responsible use of AI and technology, we aim to build a stronger, more innovative future for our nation and our people."
HH Sheikh Mohamed bin Zayed Al Nahyan, President of the UAE
"Our responsibility is to equip our children for a time unlike ours, with conditions different from ours, and with new skills and capabilities that ensure the continued momentum of development and progress in our nation for decades to come."
HH Sheikh Mohammed bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE and Ruler of Dubai
Program Overview
The Master of Science in Environmental Artificial Intelligence (MScEAI) is an interdisciplinary graduate program that integrates advanced artificial intelligence techniques with environmental science to address global sustainability challenges. It equips students with expertise in machine learning, data analytics, remote sensing, and ecological modelling to analyse complex environmental systems. The program emphasises practical applications of AI in climate change mitigation, biodiversity conservation, renewable energy optimisation, and smart resource management. Students develop strong computational skills alongside a deep understanding of environmental processes and policy frameworks. Through hands-on projects and research, learners apply AI-driven solutions to real-world environmental problems. The curriculum fosters innovation, critical thinking, and ethical responsibility in the deployment of AI technologies for environmental stewardship. Graduates are prepared for impactful careers in research, industry, government, and international sustainability initiatives.
Benefits
The MSc & PGDip in Environmental Intelligence equips graduates with cutting-edge skills in AI, remote sensing, and climate modelling to address pressing sustainability challenges at local and global levels. With the nation committed to Net Zero by 2050 and billions pledged in clean energy investment, demand for professionals who bridge environmental science and intelligent systems has never been greater. The program develops analytical fluency to translate complex environmental data into actionable policy, infrastructure, and ESG decisions across industries such as energy, construction, and urban development. Students benefit from direct engagement with landmark UAE initiatives such as the Green Agenda, Masdar City, and the Ministry of Climate Change & Environment, offering a learning environment uniquely unavailable elsewhere. A research-driven capstone thesis conducted in partnership with government bodies and industry leaders ensures graduates produce work with tangible, real-world impact.
Career Opportunities
As graduates of the MSc or PGDip in Environmental Intelligence, students will have the qualifications and skills to pursue career opportunities such as:
- Environmental data scientists
- AI specialists
- Sustainability analysts
- Research professionals in governmental, industrial, and academic sectors
The Ministry of Higher Education and Scientific Research (MoHESR) of the UAE awarded the program accreditation on April 8, 2023.
The program has five goals as follows:
Goal 1: Equip students with advanced theoretical and practical knowledge in Artificial Intelligence, Machine Learning, and Environmental Science to address complex ecological challenges.
Goal 2: Develop specialized skills in environmental data engineering, geospatial analytics, and earth observation technologies for monitoring and managing climate systems.
Goal 3: Foster independent research capabilities, enabling students to conduct innovative studies that contribute to sustainability, climate risk mitigation, and circular economy strategies.
Goal 4: Prepare graduates for leadership roles in the green economy by bridging the gap between technical AI implementation and environmental policy-making.
Goal 5: Promote the ethical and responsible use of AI in solving global environmental issues, aligning with UN Sustainable Development Goals (SDGs).
Upon successful completion of the program, the student will be able to:
PLO 1: Demonstrate advanced, integrated knowledge of artificial intelligence, mathematics, statistics, and machine learning for sustainable environmental systems.
PLO 2: Analyze, preprocess, integrate, and manage environmental datasets using robust, scalable, reproducible, and sustainable data engineering practices.
PLO 3: Design, implement, and evaluate innovative machine learning models for sustainable environmental monitoring, forecasting, and decision support.
PLO 4: Apply data-driven and artificial intelligence methods to assess environmental risks and support sustainable resilience strategies and decision-making.
PLO 5: Conduct independent research in environmental artificial intelligence to develop innovative entrepreneurial solutions and communicate findings effectively to diverse audiences.
PLO 6: Demonstrate professional responsibility, applying responsible artificial intelligence, sustainability, ethics, teamwork, leadership, and good research practice.
The Master of Science in Environmental Artificial Intelligence is offered at the CUD Campus in a full-time, regular study mode. The program is completed in 3 semesters (1.5 academic years), and the maximum duration of completion of the program is three academic years.
The MScEAI degree will be awarded to a student upon completing the following requirements:
- Successful completion of 36 credit hours.
- Achievement of a minimum CGPA of 3.0 on a 4.0 scale.
- Completion of at least 75% of the credit hours at CUD.
- Master's Thesis must be completed at CUD.
The Postgraduate Diploma in Environmental Artificial Intelligence is offered at the CUD Campus in a full-time, regular study mode. The program is completed in 1 semester (1 academic year), and the maximum duration of completion of the program is two academic years.
The Postgraduate Diploma (PGDip) degree will be awarded to a student upon completing the following requirements:
- Successful completion of 24 credit hours of coursework from the MScEAI program curriculum.
- Achievement of a minimum CGPA of 3.0 on a 4.0 scale.
- Completion of at least 75% of the credit hours at CUD.
Program Structure
The structure of the Master of Science in Environmental Artificial Intelligence program is as follows:
| Requirements | Compulsory Credit Hours |
|---|---|
| Core Courses | 21 Cr. Hrs. |
| Electives | 6 Cr. Hrs. |
| Master's Thesis and Practicum | 9 Cr. Hrs. |
| Total | 36 Cr. Hrs. |
| Course Code | Course Title | Prerequisite | Credit Hours |
|---|---|---|---|
|
Core Courses |
21 Cr. Hrs. |
||
| MAI 600 | Mathematics and Statistics for AI | None | 3 |
| MAI 602 | Machine Learning | None | 3 |
| MEI 600 | Programming for Environmental Intelligence | None | 3 |
| MEI 601 | AI for Climate Science and Environmental Systems | None | 3 |
| MEI 602 | Environmental Data Engineering | MEI 600 | 3 |
| MEI 603 | Deep Learning for Earth Observation | MAI 602 | 3 |
| MEI 604 | Research Methods in Environmental AI | MAI 600 | 3 |
| Course Code | Course Title | Prerequisite | Credit Hours |
|---|---|---|---|
|
Elective Courses |
6 Cr. Hrs. |
||
| MEI 605 | Geospatial Artificial Intelligence | MEI 601 and MAI 602 | 3 |
| MEI 606 | Urban Environmental Analytics | MEI 603 | 3 |
| MEI 607 | Sustainability Policy Analytics | MEI 602 | 3 |
| MEI 608 | Climate Risk Analytics | MAI 602 | 3 |
| MEI 609 | AI for Smart and Sustainable Cities | MEI 602 | 3 |
| MEI 610 | AI for Renewable and Smart Energy Systems | MEI 602 | 3 |
| Course Code | Course Title | Prerequisite | Credit Hours |
|---|---|---|---|
|
Practicum and Master's Thesis |
9 Cr. Hrs. |
||
| MEI 620 | Environmental Artificial Intelligence Practicum | Completed 21 Credit Hours | 3 |
| MEI 621 | Master's Thesis | Completed 21 Credit Hours including MEI 604 | 6 |